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Faster compressed quadtrees.

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Bibliographic Details
Title: Faster compressed quadtrees.
Authors: de Bernardo, Guillermo1 (AUTHOR), Gagie, Travis1,2 (AUTHOR) travis.gagie@gmail.com, Ladra, Susana1 (AUTHOR), Navarro, Gonzalo3,4 (AUTHOR), Seco, Diego1,3 (AUTHOR)
Source: Journal of Computer & System Sciences. Feb2023, Vol. 131, p86-104. 19p.
Subjects: Quadtrees, Point set theory, Multicasting (Computer networks)
Abstract: Real-world point sets tend to be clustered, so using a machine word for each point is wasteful. In this paper we first show how a compact representation of quadtrees using O (1) bits per node can break this bound on clustered point sets, while offering efficient range searches. We then describe a new compact quadtree representation based on heavy-path decompositions, which supports queries faster than previous compact structures. We present experimental evidence showing that our structure is competitive in practice. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Computer & System Sciences is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 159601463
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Faster compressed quadtrees.
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  Data: <searchLink fieldCode="AR" term="%22de+Bernardo%2C+Guillermo%22">de Bernardo, Guillermo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gagie%2C+Travis%22">Gagie, Travis</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> travis.gagie@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Ladra%2C+Susana%22">Ladra, Susana</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Navarro%2C+Gonzalo%22">Navarro, Gonzalo</searchLink><relatesTo>3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Seco%2C+Diego%22">Seco, Diego</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Computer+%26+System+Sciences%22">Journal of Computer & System Sciences</searchLink>. Feb2023, Vol. 131, p86-104. 19p.
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  Data: <searchLink fieldCode="DE" term="%22Quadtrees%22">Quadtrees</searchLink><br /><searchLink fieldCode="DE" term="%22Point+set+theory%22">Point set theory</searchLink><br /><searchLink fieldCode="DE" term="%22Multicasting+%28Computer+networks%29%22">Multicasting (Computer networks)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Real-world point sets tend to be clustered, so using a machine word for each point is wasteful. In this paper we first show how a compact representation of quadtrees using O (1) bits per node can break this bound on clustered point sets, while offering efficient range searches. We then describe a new compact quadtree representation based on heavy-path decompositions, which supports queries faster than previous compact structures. We present experimental evidence showing that our structure is competitive in practice. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Journal of Computer & System Sciences is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.jcss.2022.09.001
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 19
        StartPage: 86
    Subjects:
      – SubjectFull: Quadtrees
        Type: general
      – SubjectFull: Point set theory
        Type: general
      – SubjectFull: Multicasting (Computer networks)
        Type: general
    Titles:
      – TitleFull: Faster compressed quadtrees.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: de Bernardo, Guillermo
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            NameFull: Gagie, Travis
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            NameFull: Ladra, Susana
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            NameFull: Navarro, Gonzalo
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            NameFull: Seco, Diego
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          Dates:
            – D: 01
              M: 02
              Text: Feb2023
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 00220000
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            – Type: volume
              Value: 131
          Titles:
            – TitleFull: Journal of Computer & System Sciences
              Type: main
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